Department of Computer Science
 Rutgers University

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GenExpTimecourses: Analysis of gene expression time-courses

The molecular processes of life are dynamic over time. Microarray experiments measuring the expression levels of a multitude of genes over time are one way of gaining insight into the dynamic processes. As a first analysis groups of similar expression patterns are routinely identified. We have developed an approach which allows to use prior knowledge, is flexible and very robust to noise. The method is implemented in the software GQL which allows control of the analysis process by use of graphical user interfaces. Currently, we are extending our framework to allow integration of further data related to transcription or protein interactions. Furthermore, we are also investigating methodologies for validating clustering of genes with functional annotation.

Publications

Schilling, Ruben B and Costa, Ivan G and Schliep, Alexander. pGQL: A Probabilistic Graphical Query Language for Gene Expression Time Courses (2011) [details]

Costa, Ivan G. and Schönhuth, Alexander and Hafemeister, Christoph and Schliep, Alexander. Constrained Mixture Estimation for Analysis and Robust Classification of Clinical Time Series (2009) [details]

Schönhuth, Alexander and Costa, Ivan G. and Schliep, Alexander. Semi-supervised Clustering of Yeast Gene Expression (2009) [details]

Costa, Ivan G.. Mixture Models for the Analysis of Gene Expression: Integration of Multiple Experiments and Cluster Validation (2008) [details]

Costa, Ivan G. and Schliep, Alexander. On the feasibility of Heterogeneous Analysis of Large Scale Biological Data (2006) [details]

Costa, Ivan G. and Schönhuth, Alexander and Schliep, Alexander. The Graphical Query Language: a tool for analysis of gene expression time-courses (2005) [details]

Schliep, Alexander and Costa, Ivan G. and Steinhoff, Christine and Schönhuth, Alexander. Analyzing gene expression time-courses (2005) [details]

Schliep, Alexander and Steinhoff, Christine and Schönhuth, Alexander. Robust inference of groups in gene expression time-courses using mixtures of HMMs (2004) [details]

Schliep, Alexander and Schönhuth, Alexander and Steinhoff, Christine. Using hidden Markov models to analyze gene expression time course data (2003) [details]

Contact: Alexander Schliep (schliep@cs.rutgers.edu).